mlsanityData to 7 Oct 2026

Synthesis of Control Barrier Functions Using a Supervised Machine Learning Approach

arXiv 2003.04950 ↗First posted 10 Mar 2020cs.RO cs.SY eess.SYcited by 35

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Abstract (arXiv)

Control barrier functions are mathematical constructs used to guarantee safety for robotic systems. When integrated as constraints in a quadratic programming optimization problem, instantaneous control synthesis with real-time performance demands can be achieved for robotics applications. Prevailing use has assumed full knowledge of the safety barrier functions, however there are cases where the safe regions must be estimated online from sensor measurements. In these cases, the corresponding barrier function must be synthesized online. This paper describes a learning framework for estimating control barrier functions from sensor data. Doing so affords system operation in unknown state space regions without compromising safety. Here, a support vector machine classifier provides the barrier function specification as determined by sets of safe and unsafe states obtained from sensor measurements. Theoretical safety guarantees are provided. Experimental ROS-based simulation results for an omnidirectional robot equipped with LiDAR demonstrate safe operation.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Mar 2020.

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Citing papers per year: 2021: 9; 2022: 3; 2023: 6; 2024: 6; 2025: 8; 2026: 3.

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  1. 2021Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificatescited by 71
  2. 2025VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layercited by 32
  3. 2021Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learningcited by 25
  4. 2021Learning Robust Output Control Barrier Functions from Safe Expert Demonstrationscited by 19
  5. 2023In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution Statescited by 15
  6. 2021Learning Robust Hybrid Control Barrier Functions for Uncertain Systemscited by 14
  7. 2021BarrierNet: A Safety-Guaranteed Layer for Neural Networkscited by 11
  8. 2025SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functionscited by 11
  9. 2023Sequential Neural Barriers for Scalable Dynamic Obstacle Avoidancecited by 8
  10. 2021Reactive and Safe Road User Simulations using Neural Barrier Certificatescited by 7
  11. 2025Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Controlcited by 7
  12. 2025How to Train Your Latent Control Barrier Function: Smooth Safety Filtering Under Hard-to-Model Constraintscited by 7
23 more
  1. 2021Provably Correct Training of Neural Network Controllers Using Reachability Analysiscited by 5
  2. 2024Safe Reach Set Computation via Neural Barrier Certificatescited by 5
  3. 2021Model Free Barrier Functions via Implicit Evading Maneuverscited by 3
  4. 2022Safe Inverse Reinforcement Learning via Control Barrier Functioncited by 3
  5. 2024Learning Control Barrier Functions and their application in Reinforcement Learning: A Surveycited by 3
  6. 2024Learning Maximal Safe Sets Using Hypernetworks for MPC-based Local Trajectory Planning in Unknown Environmentscited by 3
  7. 2025Reachability Barrier Networks: Learning Hamilton-Jacobi Solutions for Smooth and Flexible Control Barrier Functionscited by 3
  8. 2022Gaussian Control Barrier Functions : A Non-Parametric Paradigm to Safetycited by 2
  9. 2023ConBaT: Control Barrier Transformer for Safe Policy Learningcited by 2
  10. 2023Learning Feasibility Constraints for Control Barrier Functionscited by 2
  11. 2025ORN-CBF: Learning Observation-conditioned Residual Neural Control Barrier Functions via Hypernetworkscited by 2
  12. 2021Safety-Critical Learning of Robot Control with Temporal Logic Specificationscited by 1
  13. 2023EnergyShield: Provably-Safe Offloading of Neural Network Controllers for Energy Efficiencycited by 1
  14. 2024Online Efficient Safety-Critical Control for Mobile Robots in Unknown Dynamic Multi-Obstacle Environmentscited by 1
  15. 2025Accelerated Learning with Linear Temporal Logic using Differentiable Simulationcited by 1
  16. 2022Geometry of Radial Basis Neural Networks for Safety Biased Approximation of Unsafe Regionscited by 0
  17. 2023Assurance for Deployed Continual Learning Systemscited by 0
  18. 2024Fault Tolerant Neural Control Barrier Functions for Robotic Systems under Sensor Faults and Attackscited by 0
  19. 2024ABNet: Attention BarrierNet for Safe and Scalable Robot Learningcited by 0
  20. 2025Worst-Case Distance-Aware Error Bounds for Neural Networkscited by 0
  21. 2026Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observationcited by 0
  22. 2026Data-Driven Time-Varying Control Barrier Functions for Adaptive Safe-Set Learning with Online Decremental Support Vector Machinescited by 0
  23. 2026VertexCBF: Improving Neural Control Barrier Functions via Vertex-Restricted Control Searchcited by 0